Convolved Substructure: Analytically Decorrelating Jet Substructure Observables

TL;DR

This paper introduces the Convolved SubStructure (CSS) method, which analytically decorrelates jet substructure observables like D2 from jet mass, enhancing their utility in searches for new particles.

Contribution

The CSS approach provides a novel, analytically derived method to decorrelate jet substructure observables from jet mass, improving analysis sensitivity.

Findings

CSS fully decorrelates D2 over a wide mass range

Analytical shape functions enable precise decorrelation

Highlights the importance of theoretical understanding in jet substructure

Abstract

A number of recent applications of jet substructure, in particular searches for light new particles, require substructure observables that are decorrelated with the jet mass. In this paper we introduce the Convolved SubStructure (CSS) approach, which uses a theoretical understanding of the observable to decorrelate the complete shape of its distribution. This decorrelation is performed by convolution with a shape function whose parameters and mass dependence are derived analytically. We consider in detail the case of the $D_2$ observable and perform an illustrative case study using a search for a light hadronically decaying $Z'$. We find that the CSS approach completely decorrelates the $D_2$ observable over a wide range of masses. Our approach highlights the importance of improving the theoretical understanding of jet substructure observables to exploit increasingly subtle features for performance.